Suciu, M.A., S., Gasko, N. & Lung, R.I. (2017) PloS One [Q2]

Publicat: 24 Noiembrie 2020

Suciu, M.A., S., Gasko, N. & Lung, R.I. (2017) Approximation of Nash equilibria and the network community structure detection problem. PloS One, 12(5), e0174963.

DOI: https://doi.org/10.1371/journal.pone.0174963

✓ Publisher: PLoS
✓ Web of Science Core Collection: Science Citation Index Expanded
✓ Categories: Multidisciplinary Sciences
✓ Article Influence Score (AIS): 1.000 (2017) / Q2

Abstract: Game theory based methods designed to solve the problem of community structure detection in complex networks have emerged in recent years as an alternative to classical and optimization based approaches. The Mixed Nash Extremal Optimization uses a generative relation for the characterization of Nash equilibria to identify the community structure of a network by converting the problem into a non-cooperative game. This paper proposes a method to enhance this algorithm by reducing the number of payoff function evaluations. Numerical experiments performed on synthetic and real-world networks show that this approach is efficient, with results better or just as good as other state-of the-art methods.

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